The Optimal Control Based on Particle Swarm Intelligence Algorithm

In order to further investigate the intelligent optimization of particle swarm optimization (pso) algorithm, we carried on the design experiments in this paper, the particle swarm optimization (pso) algorithm, the position of the first set search point X0i and speed V0i initialization; Then evaluate each particle, calculate the fitness value of particles, if is better than that of the particle current individual extremum, update the individual extremum, if in the particles of all particles in the neighborhood of the best good of individual extremum in the current record the serial number of the particles, and the update function value; For each particle velocity and position updating; The end of the final inspection is in line with the conditions, if the current number of iterations to achieve the pre-set number of maximum (or minimum error requirement), is to stop the iteration, output the optimal solution, or go to the evaluation steps, particles will eventually take the simulation control object, carries on the simulation, intelligent optimization, particle swarm algorithm is verified in engineering has a great application prospect.